In this paper, a solution for UAV localization in GPS and magnetometer denied environments is proposed. Due to its robustness and computational stability, an ES-EKF is used for reliable state estimation in the context of multi-sensor fusion. The work presented in [1]} gives an overview of quaternion kinematics and provides an intuitive insight into the technique of error state filtering and serves as a starting point for the approach proposed in this paper. The filter implementation is further extended to allow for online drift estimation. Visual and LiDAR SLAM, commonly used as pose sensing methods in the context of indoor localization, are known to accumulate drift error over time, hence the motivation to consider this in state estimation.
